Merge pull request #2488 from hlohaus/ccccc

Add get_models to GeminiPro provider

g4f/Provider/Blackbox2.py

@@ -6,7 +6,7 @@
 import json
 from pathlib import Path
 from aiohttp import ClientSession
-from typing import AsyncGenerator
+from typing import AsyncIterator
 
 from ..typing import AsyncResult, Messages
 from ..image import ImageResponse
@@ -21,12 +21,12 @@ class Blackbox2(AsyncGeneratorProvider, ProviderModelMixin):
         "llama-3.1-70b": "https://www.blackbox.ai/api/improve-prompt",
         "flux": "https://www.blackbox.ai/api/image-generator"
     }
-    
+
     working = True
     supports_system_message = True
     supports_message_history = True
     supports_stream = False
-       
+
     default_model = 'llama-3.1-70b'
     chat_models = ['llama-3.1-70b']
     image_models = ['flux']
@@ -97,15 +97,14 @@ async def create_async_generator(
         messages: Messages,
         prompt: str = None,
         proxy: str = None,
-        prompt: str = None,
         max_retries: int = 3,
         delay: int = 1,
         max_tokens: int = None,
         **kwargs
-    ) -> AsyncGenerator[str, None]:
+    ) -> AsyncResult:
         if not model:
             model = cls.default_model
-            
+
         if model in cls.chat_models:
             async for result in cls._generate_text(model, messages, proxy, max_retries, delay, max_tokens):
                 yield result
@@ -125,13 +124,13 @@ async def _generate_text(
         max_retries: int = 3, 
         delay: int = 1,
         max_tokens: int = None,
-    ) -> AsyncGenerator[str, None]:
+    ) -> AsyncIterator[str]:
         headers = cls._get_headers()
 
         async with ClientSession(headers=headers) as session:
             license_key = await cls._get_license_key(session)
             api_endpoint = cls.api_endpoints[model]
-            
+
             data = {
                 "messages": messages,
                 "max_tokens": max_tokens,
@@ -162,19 +161,19 @@ async def _generate_image(
         model: str, 
         prompt: str, 
         proxy: str = None
-    ) -> AsyncGenerator[ImageResponse, None]:
+    ) -> AsyncIterator[ImageResponse]:
         headers = cls._get_headers()
         api_endpoint = cls.api_endpoints[model]
 
         async with ClientSession(headers=headers) as session:
             data = {
                 "query": prompt
             }
-            
+
             async with session.post(api_endpoint, headers=headers, json=data, proxy=proxy) as response:
                 response.raise_for_status()
                 response_data = await response.json()
-                
+
                 if 'markdown' in response_data:
                     image_url = response_data['markdown'].split('(')[1].split(')')[0]
                     yield ImageResponse(images=image_url, alt=prompt)

g4f/Provider/Cloudflare.py

@@ -2,7 +2,6 @@
 
 import asyncio
 import json
-import uuid
 
 from ..typing import AsyncResult, Messages, Cookies
 from .base_provider import AsyncGeneratorProvider, ProviderModelMixin, get_running_loop
@@ -37,18 +36,16 @@ def get_models(cls) -> str:
         if not cls.models:
             if cls._args is None:
                 get_running_loop(check_nested=True)
-                args = get_args_from_nodriver(cls.url, cookies={
-                    '__cf_bm': uuid.uuid4().hex,
-                })
+                args = get_args_from_nodriver(cls.url)
                 cls._args = asyncio.run(args)
             with Session(**cls._args) as session:
                 response = session.get(cls.models_url)
                 cls._args["cookies"] = merge_cookies(cls._args["cookies"] , response)
                 try:
                     raise_for_status(response)
-                except ResponseStatusError as e:
+                except ResponseStatusError:
                     cls._args = None
-                    raise e
+                    raise
                 json_data = response.json()
                 cls.models = [model.get("name") for model in json_data.get("models")]
         return cls.models
@@ -64,9 +61,9 @@ async def create_async_generator(
         timeout: int = 300,
         **kwargs
     ) -> AsyncResult:
-        model = cls.get_model(model)
         if cls._args is None:
             cls._args = await get_args_from_nodriver(cls.url, proxy, timeout, cookies)
+        model = cls.get_model(model)
         data = {
             "messages": messages,
             "lora": None,

g4f/Provider/PollinationsAI.py

@@ -40,7 +40,7 @@ class PollinationsAI(OpenaiAPI):
     }
 
     @classmethod
-    def get_models(cls):
+    def get_models(cls, **kwargs):
         if not hasattr(cls, 'image_models'):
             cls.image_models = []
         if not cls.image_models:

g4f/Provider/needs_auth/Cerebras.py

@@ -16,6 +16,7 @@ class Cerebras(OpenaiAPI):
     models = [
         "llama3.1-70b",
         "llama3.1-8b",
+        "llama-3.3-70b"
     ]
     model_aliases = {"llama-3.1-70b": "llama3.1-70b", "llama-3.1-8b": "llama3.1-8b"}
 
@@ -29,14 +30,15 @@ async def create_async_generator(
         cookies: Cookies = None,
         **kwargs
     ) -> AsyncResult:
-        if api_key is None and cookies is None:
-            cookies = get_cookies(".cerebras.ai")
-        async with ClientSession(cookies=cookies) as session:
-            async with session.get("https://inference.cerebras.ai/api/auth/session") as response:
-                raise_for_status(response)
-                data = await response.json()
-                if data:
-                    api_key = data.get("user", {}).get("demoApiKey")
+        if api_key is None:
+            if cookies is None:
+                cookies = get_cookies(".cerebras.ai")
+            async with ClientSession(cookies=cookies) as session:
+                async with session.get("https://inference.cerebras.ai/api/auth/session") as response:
+                    await raise_for_status(response)
+                    data = await response.json()
+                    if data:
+                        api_key = data.get("user", {}).get("demoApiKey")
         async for chunk in super().create_async_generator(
             model, messages,
             api_base=api_base,

g4f/Provider/needs_auth/DeepInfra.py

@@ -14,7 +14,7 @@ class DeepInfra(OpenaiAPI):
     default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct"
 
     @classmethod
-    def get_models(cls):
+    def get_models(cls, **kwargs):
         if not cls.models:
             url = 'https://api.deepinfra.com/models/featured'
             models = requests.get(url).json()

g4f/Provider/needs_auth/GeminiPro.py

@@ -2,30 +2,52 @@
 
 import base64
 import json
+import requests
 from aiohttp import ClientSession, BaseConnector
 
 from ...typing import AsyncResult, Messages, ImagesType
-from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
 from ...image import to_bytes, is_accepted_format
 from ...errors import MissingAuthError
+from ...requests.raise_for_status import raise_for_status
+from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
 from ..helper import get_connector
+from ... import debug
 
 class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
     label = "Google Gemini API"
     url = "https://ai.google.dev"
-
+    api_base = "https://generativelanguage.googleapis.com/v1beta"
+
     working = True
     supports_message_history = True
     needs_auth = True
-    
+
     default_model = "gemini-1.5-pro"
     default_vision_model = default_model
-    models = [default_model, "gemini-pro", "gemini-1.5-flash", "gemini-1.5-flash-8b"]
+    fallback_models = [default_model, "gemini-pro", "gemini-1.5-flash", "gemini-1.5-flash-8b"]
     model_aliases = {
         "gemini-flash": "gemini-1.5-flash",
         "gemini-flash": "gemini-1.5-flash-8b",
     }
 
+    @classmethod
+    def get_models(cls, api_key: str = None, api_base: str = api_base) -> list[str]:
+        if not cls.models:
+            try:
+                response = requests.get(f"{api_base}/models?key={api_key}")
+                raise_for_status(response)
+                data = response.json()
+                cls.models = [
+                    model.get("name").split("/").pop()
+                    for model in data.get("models")
+                    if "generateContent" in model.get("supportedGenerationMethods")
+                ]
+                cls.models.sort()
+            except Exception as e:
+                debug.log(e)
+                cls.models = cls.fallback_models
+        return cls.models
+
     @classmethod
     async def create_async_generator(
         cls,
@@ -34,17 +56,17 @@ async def create_async_generator(
         stream: bool = False,
         proxy: str = None,
         api_key: str = None,
-        api_base: str = "https://generativelanguage.googleapis.com/v1beta",
+        api_base: str = api_base,
         use_auth_header: bool = False,
         images: ImagesType = None,
         connector: BaseConnector = None,
         **kwargs
     ) -> AsyncResult:
-        model = cls.get_model(model)
-
         if not api_key:
             raise MissingAuthError('Add a "api_key"')
 
+        model = cls.get_model(model, api_key=api_key, api_base=api_base)
+
         headers = params = None
         if use_auth_header:
             headers = {"Authorization": f"Bearer {api_key}"}

g4f/Provider/needs_auth/OpenaiAPI.py

@@ -23,13 +23,13 @@ class OpenaiAPI(AsyncGeneratorProvider, ProviderModelMixin):
     fallback_models = []
 
     @classmethod
-    def get_models(cls, api_key: str = None):
+    def get_models(cls, api_key: str = None, api_base: str = api_base) -> list[str]:
         if not cls.models:
             try:
                 headers = {}
                 if api_key is not None:
                     headers["authorization"] = f"Bearer {api_key}"
-                response = requests.get(f"{cls.api_base}/models", headers=headers)
+                response = requests.get(f"{api_base}/models", headers=headers)
                 raise_for_status(response)
                 data = response.json()
                 cls.models = [model.get("id") for model in data.get("data")]
@@ -82,7 +82,7 @@ async def create_async_generator(
         ) as session:
             data = filter_none(
                 messages=messages,
-                model=cls.get_model(model),
+                model=cls.get_model(model, api_key=api_key, api_base=api_base),
                 temperature=temperature,
                 max_tokens=max_tokens,
                 top_p=top_p,
@@ -147,4 +147,4 @@ def get_headers(cls, stream: bool, api_key: str = None, headers: dict = None) ->
                 if api_key is not None else {}
             ),
             **({} if headers is None else headers)
-        }
+        }

g4f/Provider/needs_auth/OpenaiChat.py

@@ -504,7 +504,7 @@ async def synthesize(cls, params: dict) -> AsyncIterator[bytes]:
         await cls.login()
         async with StreamSession(
             impersonate="chrome",
-            timeout=900
+            timeout=0
         ) as session:
             async with session.get(
                 f"{cls.url}/backend-api/synthesize",

g4f/gui/client/index.html

@@ -150,47 +150,47 @@ <h3>Settings</h3>
                 <label for="recognition-language" class="label" title="">Speech recognition language</label>
                 <input type="text" id="recognition-language" value="" placeholder="navigator.language"/>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="BingCreateImages-api_key" class="label" title="">Microsoft Designer in Bing:</label>
                 <textarea id="BingCreateImages-api_key" name="BingCreateImages[api_key]" placeholder="&quot;_U&quot; cookie"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="Cerebras-api_key" class="label" title="">Cerebras Inference:</label>
                 <textarea id="Cerebras-api_key" name="Cerebras[api_key]" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="DeepInfra-api_key" class="label" title="">DeepInfra:</label>
                 <textarea id="DeepInfra-api_key" name="DeepInfra[api_key]" class="DeepInfraImage-api_key" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="GeminiPro-api_key" class="label" title="">Gemini API:</label>
                 <textarea id="GeminiPro-api_key" name="GeminiPro[api_key]" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="Groq-api_key" class="label" title="">Groq:</label>
                 <textarea id="Groq-api_key" name="Groq[api_key]" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="HuggingFace-api_key" class="label" title="">HuggingFace:</label>
                 <textarea id="HuggingFace-api_key" name="HuggingFace[api_key]" class="HuggingFaceAPI-api_key" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
-                <label for="Openai-api_key" class="label" title="">OpenAI API:</label>
-                <textarea id="Openai-api_key" name="Openai[api_key]" placeholder="api_key"></textarea>
+            <div class="field box hidden">
+                <label for="OpenaiAPI-api_key" class="label" title="">OpenAI API:</label>
+                <textarea id="OpenaiAPI-api_key" name="OpenaiAPI[api_key]" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="OpenRouter-api_key" class="label" title="">OpenRouter:</label>
                 <textarea id="OpenRouter-api_key" name="OpenRouter[api_key]" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="PerplexityApi-api_key" class="label" title="">Perplexity API:</label>
                 <textarea id="PerplexityApi-api_key" name="PerplexityApi[api_key]" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="Replicate-api_key" class="label" title="">Replicate:</label>
                 <textarea id="Replicate-api_key" name="Replicate[api_key]" class="ReplicateImage-api_key" placeholder="api_key"></textarea>
             </div>
-            <div class="field box">
+            <div class="field box hidden">
                 <label for="xAI-api_key" class="label" title="">xAI:</label>
                 <textarea id="xAI-api_key" name="xAI[api_key]" placeholder="api_key"></textarea>
             </div>

g4f/gui/client/static/css/style.css

@@ -1022,7 +1022,8 @@ ul {
     }
 
     .settings h3 {
-        padding-left: 50px;
+        padding-left: 54px;
+        padding-top: 18px;
     }
 
     .buttons {

g4f/gui/client/static/js/chat.v1.js

@@ -1293,6 +1293,7 @@ const load_provider_option = (input, provider_name) => {
         providerSelect.querySelectorAll(`option[data-parent="${provider_name}"]`).forEach(
             (el) => el.removeAttribute("disabled")
         );
+        settings.querySelector(`.field:has(#${provider_name}-api_key)`)?.classList.remove("hidden");
     } else {
         modelSelect.querySelectorAll(`option[data-providers*="${provider_name}"]`).forEach(
             (el) => {
@@ -1307,6 +1308,7 @@ const load_provider_option = (input, provider_name) => {
         providerSelect.querySelectorAll(`option[data-parent="${provider_name}"]`).forEach(
             (el) => el.setAttribute("disabled", "disabled")
         );
+        settings.querySelector(`.field:has(#${provider_name}-api_key)`)?.classList.add("hidden");
     }
 };